Software Engineer, Forward Deployed AI

Software Engineer · Mid · Full Time

New York, NY (HQ)USD 189k – 330k2d ago
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Role

What you'll do.

As a Software Engineer, Forward Deployed AI at Ramp, you will co-lead customer engagements delivering enterprise AI solutions for finance operations. You'll partner directly with customers from technical discovery through production deployment, translating business goals into robust system architectures while leveraging large language models and Ramp's core platform primitives. This is a highly client-facing role requiring strong full-stack engineering skills, ML/GenAI fundamentals, and enterprise solutions architecture experience.

Responsibilities

  • Customer Technical Discovery & Requirements Translation: Partner directly with enterprise customers and end users to conduct comprehensive technical discovery of current workflows, systems, data quality, constraints, and adoption blockers. Translate customer business goals and objectives into precise system requirements and non-functional requirements covering security, privacy, reliability, performance, scalability, and total cost of ownership. Document customer needs and establish success criteria collaboratively with AI Solutions Strategist and stakeholder teams.
  • Solution Architecture & Design: Design custom AI solutions tailored to each customer's unique requirements and constraints. Create and maintain comprehensive solution architecture artifacts including system context diagrams, data flow diagrams, integration plans across Ramp and customer systems, security models covering permissions and access patterns, evaluation plans with quality metrics and acceptance criteria, and operational plans covering monitoring, alerting, incident response, and runbooks.
  • Rapid Prototyping & Validation: Prototype and validate workflows with end users to rapidly de-risk the technical approach, prove product-market fit, and gather iterative feedback. Build working prototypes that demonstrate solution feasibility, business value, and user adoption potential. Conduct red-teaming exercises and edge case analysis to validate robustness of proposed AI solutions.
  • Implementation & Production Deployment: Lead implementation of AI solutions from bootcamp phase through production launch. Leverage existing Ramp core primitives to build efficiently, reusing established product capabilities and patterns wherever possible. Write production-quality code, establish comprehensive testing strategies, and ensure systems meet security, compliance, and operational standards. Conduct technical handoff and knowledge transfer to customer operations teams.
  • LLM Systems Engineering: Build and deploy large language model systems including retrieval-augmented generation pipelines, AI agents, and prompt engineering workflows optimized for financial use cases. Implement monitoring and evaluation frameworks for assessing model performance, user adoption, and business impact. Manage model versioning, A/B testing, and continuous improvement processes for deployed AI solutions.
  • Integration & Platform Leveraging: Design and implement integrations connecting customer systems, data sources, and business processes with Ramp platform capabilities and AI solutions. Work across APIs, webhooks, event streaming, and custom data connectors. Build data pipelines ensuring data quality, reliability, and compliance with customer security and privacy requirements.
  • Production Operations & Support: Ensure deployed AI workflows are reliable, observable, and supportable in production environments. Establish monitoring, alerting, and incident response procedures. Conduct ongoing measurement of solution adoption, business impact, and customer satisfaction. Provide technical support and optimization guidance during production phase.
  • Pattern Development & Knowledge Capture: Convert customer-specific deployments into reusable patterns, components, libraries, and playbooks for future AI Solutions projects. Document lessons learned, best practices, and common architectural patterns. Contribute to product roadmap through insights gained from customer implementations and feedback.
  • Enterprise Customer Collaboration: Spend significant time engaging with customers and end users throughout project lifecycle. Conduct stakeholder alignment meetings, manage expectations, build trust through technical leadership, and maintain strong customer relationships. Co-lead customer engagements with AI Solutions Strategist partner, owning technical aspects while strategist owns business and ROI narrative.
  • Technical Documentation & Knowledge Transfer: Produce clear, comprehensive technical documentation including architecture design documents, API specifications, security documentation, operational runbooks, and training materials for customer technical teams. Ensure documentation supports ongoing operations and enables knowledge transfer to customer support and development teams.

Qualifications

What we look for.

Technical

  • ML/GenAI System Development

    Proven ability to build production machine learning and generative AI systems. Strong understanding of RAG architectures, AI agent design, prompt engineering, and evaluation methodologies. Experience decomposing complex business problems into ML/AI solutions with clear success metrics and failure mode analysis.

  • Full-Stack System Architecture

    Capability to design end-to-end systems spanning frontend integration, backend APIs, data pipelines, and cloud infrastructure. Experience with non-functional requirements including security, scalability, performance optimization, and cost management in distributed systems.

  • Enterprise Integration Engineering

    Hands-on experience integrating with multiple external systems using REST APIs, webhooks, event streaming, and custom data connectors. Understanding of data synchronization challenges, eventual consistency patterns, and reliable message delivery in financial workflows.

  • Cloud Architecture Proficiency

    Deep working knowledge of AWS, GCP, or Azure cloud services including compute, storage, networking, identity management, and security configurations. Experience deploying and scaling microservices, containerized applications, and serverless architectures in production.

  • Software Engineering Best Practices

    Demonstrated commitment to code quality, testing, documentation, and maintainability. Experience with version control workflows, code review processes, automated testing (unit, integration, end-to-end), and CI/CD pipeline management.

Education

  • Computer Science or Related Field

    Bachelor's degree in Computer Science, Engineering, Mathematics, or equivalent professional experience. Foundation in algorithms, data structures, and system design principles valued, though demonstrated ability through shipped projects prioritized over formal credentials.

Experience

  • Production Software Delivery

    Minimum 3-5 years of professional software engineering experience shipping production systems. Track record of taking ownership of complex projects end-to-end, including design, implementation, testing, and operational support.

  • Solutions Architecture or Consulting

    Demonstrated experience in technical consulting, solutions architecture, forward deployed engineering, or pre-sales engineering roles. Proven ability to translate customer business requirements into technical specifications, design custom solutions, and drive successful implementations.

  • Customer-Facing Technical Engagement

    Substantial experience working directly with enterprise customers and end users. Comfort conducting technical discovery, understanding workflows and pain points, identifying technical blockers, and communicating complex technical concepts to non-technical stakeholders.

  • ML/GenAI Project Delivery

    Hands-on experience building, deploying, and maintaining production machine learning or generative AI systems. Experience with LLM fine-tuning, RAG pipeline optimization, agent orchestration, model evaluation, and monitoring of AI solutions in production environments.

  • Enterprise Systems Integration

    2-3+ years working with enterprise systems, APIs, data pipelines, and cloud infrastructure. Experience handling complex integration challenges, data consistency requirements, security and compliance considerations in mission-critical environments.

Skills

Required

  • Machine Learning & GenAI

    Strong fundamentals in ML/GenAI including problem decomposition, evaluation frameworks, and deployment trade-offs. Hands-on experience building large language model systems, including retrieval-augmented generation (RAG), AI agents, monitoring strategies, and evaluation metrics.

  • Production Software Development

    Demonstrated experience shipping production software in high-ownership environments with end-to-end responsibility for system quality, reliability, and operational support.

  • Programming Languages

    Strong coding proficiency in at least one of Python, TypeScript/JavaScript, Java, or Go. Ability to write clean, maintainable, and well-tested code across backend and integration scenarios.

  • Solutions Architecture

    Experience in technical consulting, solutions architecture, forward deployed engineering, or pre-sales engineering roles. Ability to translate customer requirements into clear system and non-functional requirements encompassing security, privacy, reliability, performance, and scalability.

  • Cloud Infrastructure & Distributed Systems

    Hands-on experience with cloud architecture on AWS, GCP, or Azure. Understanding of distributed systems patterns, APIs, data pipelines, and integration challenges in enterprise environments.

  • Enterprise Integration

    Comfort designing secure, scalable systems that integrate across customer APIs, third-party systems, and cloud infrastructure. Ability to handle data pipelines, access control, and auditability requirements.

  • System Design & Documentation

    Proven ability to design complex systems and produce clear, comprehensive technical documentation. Experience creating architecture artifacts including data flow diagrams, integration plans, security models, and operational runbooks.

  • Customer-Facing Technical Leadership

    Ability to work directly with enterprise customers and end users, conducting technical discovery, understanding workflows and constraints, identifying adoption blockers, and driving projects from conception through production deployment and handoff.

Preferred

  • Finance Operations Domain Knowledge

    Nice to have

    Familiarity with finance operations workflows and processes such as accounts payable, procurement, expense management, close procedures, reconciliation, and financial reporting. Understanding of spend management, payment authorization, and risk flagging in financial systems.

  • LLM Deployment & Monitoring

    Nice to have

    Experience monitoring and maintaining deployed language model systems in production, including performance tracking, quality metrics, incident response, and user adoption measurement.

  • Pre-Sales Engineering

    Nice to have

    Background in technical pre-sales, proof-of-concept development, or customer success engineering roles where you've influenced product decisions through customer feedback and technical validation.

  • Data Quality & Evaluation

    Nice to have

    Experience working with data quality issues, designing evaluation frameworks for AI/ML systems, conducting red-teaming, and establishing acceptance criteria and metrics for production AI deployments.

Tech stack

Languages

PythonTypeScript/JavaScriptJavaGo

Frameworks

LLM FrameworksAPI FrameworksRAG & Vector Systems

Databases

Relational DatabasesVector DatabasesData Warehouses

Tools

Cloud PlatformsVersion Control & CI/CDMonitoring & ObservabilityInfrastructure as Code

Other

API Integration & OrchestrationMLOps & Model EvaluationSecurity & Compliance

Compensation

Pay and benefits.

Base·USD 189,000 – 330,000

Equity·Stock options

Full posting

Original listing.

About Ramp

Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books.

The problems are high-stakes, data-dense, and unforgiving.

We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome.

The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same.

If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it.

About the Role

As a software engineer on the AI Soltuions team, you will co-lead customer engagements with an AI Solutions Strategist. The Strategist owns business discovery, ROI narrative, stakeholder alignment, and rollout planning. The engineer owns technical discovery, solution design, prototyping, implementation, and production readiness.

This is a deeply client-facing role. You will spend significant time with customers and end users, moving projects from bootcamp and workflow discovery through implementation, launch, and steady production usage.

What You’ll Do

  • Translate customer goals into clear system requirements and non-functional requirements covering security, privacy, reliability, performance, scalability, and cost.

  • Partner directly with customers to understand current workflows, constraints, systems, data quality, and adoption blockers.

  • Create and maintain solution architecture artifacts:

    • System context and data flow diagrams

    • Integration plan across Ramp and customer systems

    • Security model covering permissions, access patterns, and auditability

    • Evaluation plan covering quality metrics, acceptance tests, and red-teaming

    • Operational plan covering monitoring, alerting, incident response, and runbooks

  • Leverage core Ramp primitives to build efficiently, reusing existing product capabilities wherever possible.

  • Prototype and validate workflows with end users to de-risk the approach and prove product-market fit.

  • Drive projects from bootcamp and technical discovery through implementation, production launch, and operational handoff.

  • Ensure deployed workflows are reliable, supportable, measurable, and adopted by customer teams.

  • Convert deployments into reusable patterns, components, and playbooks for future AI Solutions projects.

What You Need

  • Experience shipping production software in high-ownership environments.

  • Ability to work directly with enterprise customers from discovery through production implementation.

  • Experience in solutions architecture, technical consulting, forward deployed engineering, or pre-sales engineering.

  • Strong fundamentals in ML/GenAI, including problem decomposition, evaluation, and deployment trade-offs.

  • Strong coding ability in at least one of: Python, TypeScript/JavaScript, Java, Go, or similar.

  • Ability to design secure, scalable systems and produce clear technical documentation.

  • Comfort working across APIs, integrations, data pipelines, customer systems, and cloud infrastructure.

  • Experience with cloud architecture on AWS, GCP, or Azure, and distributed systems patterns.

  • Experience building LLM systems, including RAG, agents, monitoring, and evals.

  • Willingness to travel up to ~75% as needed, flexible based on project needs and client needs

  • Nice to have: Familiarity with finance operations workflows such as AP, procurement, expenses, close, reconciliation, and reporting.

Benefits available to all full-time Ramp employees (Global)

  • Flexible PTO

  • Centralized home-office equipment ordering

  • Health and wellness stipend

  • Budget for intra-office travel

  • Weekly coffee stipend

United States

  • 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents

  • One Medical annual membership

  • 401(k), including employer match on contributions made while employed by Ramp

  • Fertility HRA (up to $10,000 per year)

  • Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay

  • Pet insurance

  • In-office perks: lunch, snacks, drinks, and more

  • Relocation support to NYC or SF (as needed)

Canada

  • Group medical, dental, and vision coverage through Sun Life

  • Life, AD&D, and disability coverage

  • Fertility drug coverage (up to $4,000 lifetime)

  • Group Retirement Plan with employer match (RRSP + DPSP)

  • Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay

  • Employee Assistance Program and virtual care through Lumino Health

United Kingdom

  • Private medical insurance through Freedom Elite

  • Virtual GP and at-home care via eMed x Livi

  • Workplace pension through Penfold, with salary sacrifice option

  • Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay

Referral Instructions

If you are being referred for the role, please contact that person to apply on your behalf.

 

Other notices

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

 

Beware of recruiting scams: Ramp will only contact you through official @Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.

 

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